import gradio as gr
import subprocess
import os 

os.system("rvc init")
os.system("rvc env create")
os.system("rvc dlmodel")


def rvc_infer(model, input_wav, fu, fmethod):
    output_wav = "output.wav"  # Define a path for the output file
    command = f"rvc infer -m {model} -i {input_wav} -o {output_wav} -fu {fu} -fm {fmethod}"
    result = subprocess.run(command, shell=True, capture_output=True, text=True)
    return output_wav, result.stdout

with gr.Blocks() as demo:
    gr.Markdown("# RVC `pip` Demo")
    
    with gr.Row():
        model_path = gr.File(label="Model file")
    with gr.Row():
        input_audio = gr.Audio(label="Input Audio", type="filepath")
    with gr.Row():
        fu_value = gr.Slider(label="pitch", minimum=-12, maximum=12, step=1, value=0)
    with gr.Row():
        f0_value = gr.Dropdown(choise=["pm", "crepe", "rmvpe", label="F0 method", value="rmvpe")

    
    output_audio = gr.Audio(label="Output Audio")
    command_output = gr.Textbox(label="Command Output")

    def infer(model, input_wav, fu, fmethod,fmethod):
        output_wav, result = rvc_infer(model, input_wav, fu,fmethod)
        return output_wav, result

    infer_button = gr.Button("Run Inference")
    infer_button.click(infer, inputs=[model_path, input_audio, fu_value,f0_value], outputs=[output_audio, command_output])

demo.launch()